The DPAC Cambridge Data Processing Centre (DPCI) is responsible for the photometric calibration of the Gaia data including the low resolution spectra. The large data volume produced by Gaia (~26 billion transits/year), the complexity of its data stream and the self-calibrating approach pose unique challenges for scalability, reliability and robustness of both the software pipelines and the operations infrastructure. DPCI has been the first in DPAC to realise the potential of Hadoop and Map/Reduce and to adopt them as the core technologies for its infrastructure. This has proven a winning choice allowing DPCI unmatched processing throughput and reliability within DPAC to the point that other DPCs have started following our footsteps. In this talk we will present the software infrastructure developed to build the distributed and scalable batch data processing system that is currently used in production at DPCI and the excellent results in terms of performance of the system.